Evolutionary learning of the optimal pricing strategy in an artificial payment card market

Biliana Alexandrova-Kabadjova, Edward Tsang, Andreas Krause

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Citations (Scopus)

Abstract

This chapter introduces an artificial payment card market in which we model the interactions between consumers, merchants and competing card issuers with the aim of determining the optimal pricing structure for card issuers. We allow card issuers to charge consumers and merchants fixed fees, provide net benefits from card usage and engage in marketing activities. The demand by consumers and merchants is only affected by the size of the fixed fees and the optimal pricing structure consists of a sizeable fixed fee to consumers, no fixed fee to merchants, negative net benefits to consumers and merchants as well as a high marketing effort.
Original languageEnglish
Title of host publicationNatural Computing in Computational Finance
EditorsA Brabazon, M O'Neill
PublisherSpringer
Pages233-251
ISBN (Print)9783540774761
DOIs
Publication statusPublished - 2008

Publication series

NameStudies in Computational Intelligence
NumberPart III
Volume100

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    Alexandrova-Kabadjova, B., Tsang, E., & Krause, A. (2008). Evolutionary learning of the optimal pricing strategy in an artificial payment card market. In A. Brabazon, & M. O'Neill (Eds.), Natural Computing in Computational Finance (pp. 233-251). (Studies in Computational Intelligence; Vol. 100, No. Part III). Springer. https://doi.org/10.1007/978-3-540-77477-8_13